Shortest Power Line Route Search By Using Breadth-First Algorithm and Georeferencing

As it is already known, the proper power system development represents one of the major topics of interest in the engineering community in the circumstances dictated by the transition towards the dominant production from the renewable sources and the sustainable vision of the future power systems. In order to achieve that, the engineers have to conduct various analyses, evaluating the impact that the new elements that may be introduced in the system could have on the indicators of its operation. However, for this to happen, those engineers need to have as accurate information on the relevant parameters of that element as possible, with the technical characteristics of the new power line being directly proportional to the length of that same line. Nonetheless, the estimation of the length of the new line in advance proves to be difficult even for the experts, with a large number of them turning towards the empirical methods, which can, depending on the concrete situation, cause either smaller or larger mistakes and, in some cases, even harm the reliability of the obtained results. To avoid that, this paper introduces the technique for the proposal of the optimal route for the new line between the two selected nodes of the system, based on breadth-first algorithm and the georeferenced projection of that system. This, in turn, allows the inclusion of the zones through which the line is not permitted to pass, such as the cities or the protected habitats, for example, and also provides opportunity to expand the regularly adopted two-dimensional definition of the line’s length to the three-dimensional space, since the heights of the terrain sections can also be included in the calculations. That, along with the ease of modifications and adaptations to different systems, could make the described technique a strong asset for the system planning engineers and the way of ensuring that the commonly used software tools for the grid development have the precise input data, mitigating the risk of the benefits of some of the projects ending up misinterpreted or overestimated due to the wrong assumptions related to the parameters of the lines.